The original study was conducted to determine and understand the factors that cause an increase
in the level of fatigue among aestheticians working in skin care salons. Among these factors the researchers chose to focus on the qualities associated with an aesthetician's service along with their working environment and shoe type. The study was conducted from March 15, 2003 to April 15, 2003 among 15 aestheticians in a skin care salon in the metropolitan area of Seoul.
The research was conducted and data was gathered over a 30 day period, using a fatigue level questionnaire, shoe-type questionnaire, various physical and physiological survey, clinical thermometers, a digital hemodynamomter, a measurement of the swelling of the lower limbs, tape measure, and a log of a day's total walking distance through the use of a step measuring
instrument. The obtained data and logistics were then calculated and analyzed calculated and reduced, keeping in mind the probable result according to the levels of fatigue.
-200612×high blood pressure＋1.0622×low blood pressure＋1.4194×middle crus sore edema＋ 2.3474×ankle edema＋(-1.3887)×instep swelling. The data was calculated with the following results and conclusions.
1) Inappropriate working environment, continuous work and the type of shoes worn were found to have a positive effect on the amount of muscle strain, tension and muscle fatigue that occurred along with one's fascia together with musculoskeletal system aches. Three types of shoes were considered platform sandals, nursing shoes and house slippers. Platform sandals were found to create the highest level of fatigue (3.229166), nursing shoes (-0.12213) and house slippers were found to create the lowest level of fatigue (-1.06141). House slippers were found to decrease calf muscle gastrocnemius muscle and the feeling of weakness and fatigue. Consideration was also made to the possibility that the type of shoes worn could cause an increase in fatigue and shoulder and hip pain.
2) Working environment (P＜0.0045), career starting age (P＜0.0033), career (P＜0.0248), working time (P＜0.0430) and weight (P＜0.0197) were found to have an effect on the fatigue variable, while smoking (0.0771), drinking (0.7793), height(0.4178), working time (0.6026), work place (0.4619) and other controlled variables (0.9595) were not found to be significant variables.